Update app.py

app.py

@@ -65,8 +65,6 @@ def glb_to_data_url(glb_path: str) -> str:
 # ---------------------------
 # Sambanova DeepseekR1 Clients and Chat Function
 # ---------------------------
-
-#deepseek-ai/DeepSeek-R1-Distill-Llama-70B
 sambanova_client = openai.OpenAI(
     api_key=os.environ.get("SAMBANOVA_API_KEY"),
     base_url="https://api.sambanova.ai/v1",
@@ -130,7 +128,6 @@ class Model:
         self.device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
         self.pipe = ShapEPipeline.from_pretrained("openai/shap-e", torch_dtype=torch.float16)
         self.pipe.to(self.device)
-        # Ensure the text encoder is in half precision to avoid dtype mismatches.
         if torch.cuda.is_available():
             try:
                 self.pipe.text_encoder = self.pipe.text_encoder.half()
@@ -139,7 +136,6 @@ class Model:
 
         self.pipe_img = ShapEImg2ImgPipeline.from_pretrained("openai/shap-e-img2img", torch_dtype=torch.float16)
         self.pipe_img.to(self.device)
-        # Use getattr with a default value to avoid AttributeError if text_encoder is missing.
         if torch.cuda.is_available():
             text_encoder_img = getattr(self.pipe_img, "text_encoder", None)
             if text_encoder_img is not None:
@@ -147,7 +143,6 @@ class Model:
 
     def to_glb(self, ply_path: str) -> str:
         mesh = trimesh.load(ply_path)
-        # Rotate the mesh for proper orientation
         rot = trimesh.transformations.rotation_matrix(-np.pi / 2, [1, 0, 0])
         mesh.apply_transform(rot)
         rot = trimesh.transformations.rotation_matrix(np.pi, [0, 1, 0])
@@ -379,7 +374,7 @@ def clean_chat_history(chat_history):
 # ---------------------------
 # Stable Diffusion XL Pipeline for Image Generation 
 # ---------------------------
-MODEL_ID_SD = os.getenv("MODEL_VAL_PATH") #SG161222/RealVisXL_V5.0_Lightning
+MODEL_ID_SD = os.getenv("MODEL_VAL_PATH")
 MAX_IMAGE_SIZE = int(os.getenv("MAX_IMAGE_SIZE", "4096"))
 USE_TORCH_COMPILE = os.getenv("USE_TORCH_COMPILE", "0") == "1"
 ENABLE_CPU_OFFLOAD = os.getenv("ENABLE_CPU_OFFLOAD", "0") == "1"
@@ -593,7 +588,7 @@ def generate(
     # --- DeepSeek-R1 branch ---
     if text.strip().lower().startswith("@deepseekr1"):
         prompt = text[len("@deepseekr1"):].strip()
-        yield "🔍 Querying DeepSeek-R1..."
+        # Directly return the response from the API
         response = chat_response(prompt)
         yield response
         return